Literature DB >> 29076357

Evaluating Brain-Computer Interface Performance in an ALS Population: Checkerboard and Color Paradigms.

David B Ryan1, Kenneth A Colwell2, Chandra S Throckmorton2, Leslie M Collins2, Kevin Caves2, Eric W Sellers1.   

Abstract

The objective of this study was to investigate the performance of 3 brain-computer interface (BCI) paradigms in an amyotrophic lateral sclerosis (ALS) population (n = 11). Using a repeated-measures design, participants completed 3 BCI conditions: row/column (RCW), checkerboard (CBW), and gray-to-color (CBC). Based on previous studies, it is hypothesized that the CBC and CBW conditions will result in higher accuracy, information transfer rate, waveform amplitude, and user preference over the RCW condition. An offline dynamic stopping simulation will also increase information transfer rate. Higher mean accuracy was observed in the CBC condition (89.7%), followed by the CBW (84.3%) condition, and lowest in the RCW condition (78.7%); however, these differences did not reach statistical significance ( P = .062). Eight of the eleven participants preferred the CBC and the remaining three preferred the CBW conditions. The offline dynamic stopping simulation significantly increased information transfer rate ( P = .005) and decreased accuracy ( P < .000). The findings of this study suggest that color stimuli provide a modest improvement in performance and that participants prefer color stimuli over monochromatic stimuli. Given these findings, BCI paradigms that use color stimuli should be considered for individuals who have ALS.

Entities:  

Keywords:  EEG; P300 event-related potential; assistive devices; brain-computer interface; rehabilitation

Mesh:

Year:  2017        PMID: 29076357     DOI: 10.1177/1550059417737443

Source DB:  PubMed          Journal:  Clin EEG Neurosci        ISSN: 1550-0594            Impact factor:   1.843


  3 in total

Review 1.  Brain-computer interfaces for amyotrophic lateral sclerosis.

Authors:  Dennis J McFarland
Journal:  Muscle Nerve       Date:  2020-06       Impact factor: 3.217

2.  Mitigating the Impact of Psychophysical Effects During Adaptive Stimulus Selection in the P300 Speller Brain-Computer Interface.

Authors:  Xinlin J Chen; Leslie M Collins; Boyla O Mainsah
Journal:  Annu Int Conf IEEE Eng Med Biol Soc       Date:  2021-11

3.  SSVEP BCI and Eye Tracking Use by Individuals With Late-Stage ALS and Visual Impairments.

Authors:  Betts Peters; Steven Bedrick; Shiran Dudy; Brandon Eddy; Matt Higger; Michelle Kinsella; Deirdre McLaughlin; Tab Memmott; Barry Oken; Fernando Quivira; Scott Spaulding; Deniz Erdogmus; Melanie Fried-Oken
Journal:  Front Hum Neurosci       Date:  2020-11-20       Impact factor: 3.169

  3 in total

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